Another advantage of this approach is that the modules (i.e., estimators) can be independently developed by leveraging training data if available. For example, estimating the relationship between the query and the candidate sentences can be formulated as an extractive QA task (to be described in Section REF ), which aims to detect the answer span for a query from a set of pre-selected sentences [1]}, [2]} or text passages [3]}, [4]}. Thus, the evidence estimator can be trained by leveraging distant supervision signals from existing QA datasets, including WikiQA [2]}, TrecQA [1]} and SQuAD 2.0 [3]}.
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